Unique ID: 2015014
| Division: | Coordination administrative & big data |
|---|---|
| Issue Date: | February 13th 2019 |
| Last modified: | February 22nd 2019 |
Cost: FREE
Using scanner data for consumer prices
Using scanner data for consumer prices.
Statistical Area
Project Sources
| Type Of Institution: | National statistical office |
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| Big Data Source: | Scanner data |
| Region: | Europe & Central Asia |
| Country Area: | Belgium |
| Id Country Regional: | country |
Partnerships
| Other Partners: | Other |
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| Partnership Comments: | Food retail companies (supermarket chains). |
Accessing Data
| Data Access Rights: | Only for this project |
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| Data Access Comments: | Only objective, at the moment, is calculation of consumer price indices. |
Data Coverage
| Data Coverage: | All available data |
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| Coverage Geo Pop: | Whole country / high % of market |
| Cost Implication: | Free |
| Coverage Period: | Since January 2015, start of statistical production stage. |
Project Details
| Frequency Comments: | Data come in on a weekly basis with each incoming dataset, for each of the three providers, of a size of approximately 1.5 GB (about 20 GB per month and 240 GB annually). |
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Data Quality
| Quality Framework: | Quality of output statistics |
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| Quality Aspects Evaluated: | Privacy and Security, Completeness, Usability, Time Factors, Accuracy, including selectivity |
| Validation Comments: | Data are prices for specific items, identical to previous data available (just a lot more), no conceptual or interpretation issues. |
| Quality Framework Comments: | Quality of source/input: prices from the datasets have been validated against manually collected prices, old method; turnover data have been verified for consistency over time. Quality of output statistics: simulations on scanner data have been compared with manual price collection; differences between the two have been examined in detail. |
Methodology
| Methods Used: | Traditional statistical methods |
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| Methods Comments: | Regular CPI calculations using new source. |
Technologies
| Technologies: | Relational database |
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Other
| Income Level: | High-income |
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| Iso: | BE |
| Timeframe To Produce Indicator: | NA |
| Frequency Comments: | Data come in on a weekly basis with each incoming dataset, for each of the three providers, of a size of approximately 1.5 GB (about 20 GB per month and 240 GB annually). |
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